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Who is better suited for an AI product management role compared to a traditional pm role?

3 Answers
Savita Kini
Savita Kini
Cisco Director of Product Management, Speech and Video AIMarch 3

This is not a simple question. There is no such thing as a "traditional PM" because PM roles and responsibilities differ by industry segment. There are substantial differences in PM roles from consumer app to enterprise app to hardware and enterprise infrastructure. 

Fundamentally the role of the PM is still the same - to consider customer problems, potential solution approaches, and lead them from concept to launch and facilitate a continous innovation lifecycle. The only difference here in AI/ML PM is a new approch to solving the problem with AI/ML tools and frameworks. So anyone with a "Learning mindset", ability to pick up on the AI/ML technologies and comfortable in ambiguity as this field is still growing, -- would do very well. 

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Suhas Manangi
Suhas Manangi
Airbnb Group Product ManagerJune 7

5 years from now, likely there is going to be no difference between a Traditional PM and AI PM. AI is going to be used/present in all products. I see "Traditional PM role" as a foundational one to have, upon which one can grow to become a good AI PM. Good Traditional PM with aptitude for tech and data science is likely to do well as a good AI PM. Taking a Udemy course on basics of AI/ML, and applying to every day PM job will be a great start.

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Mike Flouton
Mike Flouton
GitLab VP, ProductJanuary 9

I've often said that PM is misunderstood as a relatively junior and technical job. It's actually best when it's treated as a strategic function, and being technical is a bonus but not necessarily the be all end all.

I do think AI PM might be a bit of an exception to the last piece. You need to understand the enabling technology a bit better as an AI PM than as a PM in other domains. So I'd say you need to have the desire an ability to get into the weeds a bit. To be clear, the intent here is in no way to trample on the authority of you engineering counterparts. Always let them own the "how." But being fluent in AI will let you have much more meaningful technical tradeoff conversations.

As for where to learn, I learn best by doing. I worked my way through a book on ML models in python several years ago and had a blast and got a better sense of the art of the possible. If you're the type that learns better in structured learning there are great courses online or at local universities.

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